Risk-based evaluation of machine learning-based classification methods used for medical devices [0.03%]
基于风险的医学设备中基于机器学习的分类方法评估
Martin Haimerl,Christoph Reich
Martin Haimerl
Background: In the future, more medical devices will be based on machine learning (ML) methods. In general, the consideration of risks is a crucial aspect for evaluating medical devices. Accordingly, risks and their assoc...
Comparing conventional and Bayesian workflows for clinical outcome prediction modelling with an exemplar cohort study of severe COVID-19 infection incorporating clinical biomarker test results [0.03%]
临床结局预测建模的常规方法和贝叶斯工作流程的比较——以严重COVID-19感染队列研究为例，包括临床生物标志物检测结果
Brian Sullivan,Edward Barker,Louis MacGregor et al.
Brian Sullivan et al.
Purpose: Assessing risk factors and creating prediction models from real-world medical data is challenging, requiring numerous modelling decisions with clinical guidance. Logistic regression is a common model for such stu...
Observational Study
BMC medical informatics and decision making. 2025 Mar 10;25(1):123. DOI:10.1186/s12911-025-02955-3 2025
Advancing AI-driven thematic analysis in qualitative research: a comparative study of nine generative models on Cutaneous Leishmaniasis data [0.03%]
推动AI驱动的主题分析在定性研究中的应用：对九种生成模型在皮肤利什曼病数据上的比较研究
Issam Bennis,Safwane Mouwafaq
Issam Bennis
Background: As part of qualitative research, the thematic analysis is time-consuming and technical. The rise of generative artificial intelligence (A.I.), especially large language models, has brought hope in enhancing an...
Power asymmetry and embarrassment in shared decision-making: predicting participation preference and decisional conflict [0.03%]
共享决策中的权力不对称与窘迫：预测参与偏好和决策冲突
Karin Antonia Scherer,Björn Büdenbender,Anja K Blum et al.
Karin Antonia Scherer et al.
Background: Shared decision-making (SDM) is the gold standard for patient-clinician interaction, yet many patients are not actively involved in medical consultations and hesitate to engage in decisions on their health. De...
Development of a generic decision guide for patients in oncology: a qualitative interview study [0.03%]
肿瘤学患者通用决策指南的开发：一项定性访谈研究
Lia Schilling,Jana Kaden,Isabel Bán et al.
Lia Schilling et al.
Background: Many patients with cancer want to be involved in healthcare decisions. For adequate participation, awareness of one's own desires and preferences and sufficient knowledge about medical measures are indispensab...
Dandan Ge,Yong Xia,Zhonghua Zhang
Dandan Ge
Background: The medical record homepage represents the core and quintessential distillation of the entire medical record. This study aims to investigate the problems with the medical record homepages data quality after th...
An intelligent multi-attribute decision-making system for clinical assessment of spinal cord disorder using fuzzy hypersoft rough approximations [0.03%]
一种用于通过模糊超软粗糙近似评估脊髓疾病临床诊断的多属性决策系统
Muhammad Abdullah,Khuram Ali Khan,Atiqe Ur Rahman
Muhammad Abdullah
The data for diagnosing spinal cord disorder (SCD) are complex and often confusing, making it difficult for established diagnostic techniques to yield reliable results. This issue frequently necessitates expensive testing to get an accurate...
Retinal vein occlusion risk prediction without fundus examination using a no-code machine learning tool for tabular data: a nationwide cross-sectional study from South Korea [0.03%]
无需眼底检查的视网膜静脉阻塞风险预测：使用无代码机器学习工具进行全国横断面研究（韩国）
Na Hyeon Yu,Daeun Shin,Ik Hee Ryu et al.
Na Hyeon Yu et al.
Background: Retinal vein occlusion (RVO) is a leading cause of vision loss globally. Routine health check-up data-including demographic information, medical history, and laboratory test results-are commonly utilized in cl...
A systematic review of large language model (LLM) evaluations in clinical medicine [0.03%]
临床医学中大型语言模型(LLM)评估的系统性回顾
Sina Shool,Sara Adimi,Reza Saboori Amleshi et al.
Sina Shool et al.
Background: Large Language Models (LLMs), advanced AI tools based on transformer architectures, demonstrate significant potential in clinical medicine by enhancing decision support, diagnostics, and medical education. How...
AI-Driven decision-making for personalized elderly care: a fuzzy MCDM-based framework for enhancing treatment recommendations [0.03%]
基于人工智能的个性化老年护理决策：一个模糊多准则决策框架以提高治疗建议的质量
Abeer Aljohani
Abeer Aljohani
Background: Global healthcare systems face enormous challenges due to the ageing population, demanding novel measures to assure long-term efficacy and viability. The expanding senior population, which requires specialised...